Part 1 – Introducing the Problem

The Underappreciated Role of Distributed Ledger Technology in Disaster Resilience and Recovery: Paving the Way for Future-Proof Emergency Management Systems

Blockchain’s Blind Spot: Why Disaster Resilience Isn’t on Crypto’s Radar—Yet

Despite the ever-expanding universe of blockchain applications—from decentralized finance (DeFi) and DAOs to on-chain gaming and AI integration—there remains a glaring blind spot: the role of distributed ledger technology (DLT) in disaster resilience and recovery systems. It’s not just underdeveloped; it’s virtually ignored. And yet, it is precisely in these moments of systemic failure—natural disasters, infrastructure collapse, or humanitarian crises—where the foundational traits of blockchain technology could offer the most value: immutability, decentralization, and transparency.

Historically, disaster management has been plagued by inefficiency, opacity, and corruption. Relief distribution data is often siloed or lost; identity systems collapse when needed most; allocation transparency vanishes amid urgency. Centralized legacy systems have repeatedly failed to deliver real-time, verifiable coordination. Haiti’s 2010 earthquake and the subsequent aid mismanagement is a textbook example—billions in aid flowed in, with surprisingly little traceability or long-term impact. Yet, the crypto community has remained disengaged, focusing instead on speculative asset growth and token engineering.

Why? Primarily because the development incentives in this area are misaligned. Disaster resilience is a domain with poor monetization hooks and high institutional friction—traits that do not align with the rapid ROI of gamified Web3 projects or the capital influx from DeFi liquidity providers. Additionally, most DLT frameworks are built for stable environments, not for high-stakes volatility inherent to crisis zones. This makes disaster resilience a technological and infrastructural outlier.

Even when ideas like NFT-based donor verification or decentralized identity (DID) for displaced populations are proposed, they remain half-baked proofs-of-concept at best. There’s also a data availability issue—intermittent connectivity, offline verification, and sensor data integration present logistical barriers that most chains are not engineered to handle natively. Without native offline-first design patterns, most Layer-1 and Layer-2 protocols fall flat.

Ironically, this overlooked niche may represent one of blockchain’s strongest real-world justifications. A robust system capable of coordinating aid, validating identities, and ensuring transparent financial flows in compromised conditions could become a crucial layer in global infrastructure.

And still, a meaningful roadmap has yet to surface.

As we dive further into this series, we’ll begin exploring whether any current architectures—even those not purpose-built for catastrophe use cases—can stretch to fit the mold. Among them, projects like Agoric might hold unexpected promise due to their composability layer, as explored in A Deepdive into Agoric.

Part 2 – Exploring Potential Solutions

Blockchain Innovations for Emergency Systems: Models with Promise—And Pitfalls

From immutable audit trails to programmable money, several blockchain-driven and cryptographic models are being explored to bolster disaster resilience. Below, we evaluate three key emerging approaches: decentralized identity stacks, tokenized aid distribution, and blockchain-based resource coordination layers.

1. Verifiable Credentials for Emergency Identity Verification

Decentralized identity (DID) frameworks such as those built on W3C standards offer disaster victims a cryptographically verifiable way to prove identity without centralized databases. Projects exploring this include Sovrin and KILT.

Strengths: Eliminates dependency on physical documents vulnerable to destruction. Compatible with self-sovereign identity models enabling swift onboarding to recovery systems, including housing and healthcare.

Weaknesses: Adoption bottlenecks remain, especially from state infrastructure. In crisis-induced connectivity blackouts, the availability of wallets or nodes can become a critical point of failure. Integration with non-blockchain institutions is still theoretical at best.

2. Smart Contract-Based Aid Disbursement

Platforms leveraging programmable tokens for conditional fund releases provide opportunities for transparent disaster aid, especially when deployed on EVM-compatible chains. Agoric’s hardened smart contracts feature here due to their event-driven architecture, ideal for real-time triggers during disaster response. For more context on Agoric’s model, check out https://bestdapps.com/blogs/news/exploring-bld-the-heart-of-agorics-tokenomics.

Strengths: Enables frictionless fund routing based on predefined criteria—like GPS coordinates, flood alerts, or oracles. Traceability is granular, mitigating fraud.

Weaknesses: Dependency on reliable oracles remains a systemic issue. Without robust governance, smart contract misconfiguration can lead to locked or misrouted resources. Also, local trust in crypto rails for real-life aid remains a cultural barrier.

3. On-Chain Logistics Coordination via Multi-Stakeholder DAOs

By modeling resource coordination efforts (like food, water, shelter) as DAO proposals and execution states, multi-party workflows could be streamlined even in fragmented disaster zones.

Strengths: Offers a transparent, tamper-resistant execution record of who is doing what. Multi-sig mechanisms can prevent unilateral decision-making under duress.

Weaknesses: Governance gridlock is a real risk—especially when facing urgent deployment timelines. Human-centric edge cases (like unsafe on-chain delay) challenge the deterministic model. Interoperability between DAO tooling and traditional emergency systems (like supply chain software) is nascent.

Each proposed model shows promise, yet none are plug-and-play. The next section will examine how these technologies have (or haven't) worked in real-world deployments—from hurricane relief to war zones.

Part 3 – Real-World Implementations

On-Chain Emergency Response: Case Studies in Blockchain-Powered Crisis Management

When Cyclone Harold ravaged parts of the South Pacific, ReliefChain, a modular blockchain solution built on Tendermint consensus, partnered with local NGOs to deploy a real-time asset tracking system. The project aimed to prevent logistical failures that typically slow down aid delivery. By tokenizing relief inventory and leveraging distributed ledgers for last-mile visibility, the system successfully reduced duplicate shipments by 27%. However, integrating this blockchain with existing mobile networks was a critical bottleneck. Without persistent connectivity, data synchronization often lagged by hours, undermining the “real-time” goal of the initiative.

Likewise, GeoResQ, a startup leveraging IPFS and Filecoin for geospatial data storage in earthquake-prone regions, built a decentralized alert system. Designed to remain operational during infrastructure blackouts, the system ingested seismic sensor data and stored encrypted triggers on-chain. Theoretically elegant, the system struggled with latency due to propagation delays across Filecoin’s storage nodes. In disaster settings where seconds count, these delays raised existential questions about the viability of pure Web3 storage solutions for time-critical data.

Another attempt, a disaster insurance DAO built on the Cosmos SDK stack and integrated with oracles from Chainlink, attempted to automate post-catastrophe micro-payouts. While the DAO model suited democratically governed financial relief, sourcing accurate and tamper-proof damage data proved problematic. The automated claims resolution engine was circumvented in multiple cases by data manipulation via third-party oracles, highlighting the fragility of relying on single-point oracle data for mission-critical decisions. This scenario underscores the importance of robust, decentralized oracle networks — a topic explored further in our analysis of The Overlooked Role of Decentralized Oracles in Expanding the Blockchain Ecosystem and Enhancing Smart Contract Functionality.

Still, not every rollout met insurmountable friction. Agoric, integrating hardened JavaScript smart contracts, demonstrated promise in disaster response coordination models where actors from multiple jurisdictions needed to execute permissioned actions. Their contract composability allowed for dynamic logic modifications without jeopardizing execution integrity — something not easily achieved on monolithic EVM chains. Agoric’s unique take on decentralization is explored in A Deepdive into Agoric.

Yet even with partial successes, broader implementations remain inhibited by cross-chain compatibility challenges and UX friction during onboarding, especially among non-technical responders. The need for gas fees under duress further complicates matters, emphasizing the potential utility of feeless layer-1s or warrants for future exploration — possibly through integration with exchanges using referral programs like Binance.

Exploring where these experiments offer insight into long-term shifts toward resilient Web3 disaster frameworks requires zooming out to assess systemic evolution—a topic reserved for Part 4.

Part 4 – Future Evolution & Long-Term Implications

Future-Proofing Disaster Response: The Shifting Landscape of DLT Scalability and Integration

As disaster resilience moves increasingly toward decentralized infrastructure, the evolution of distributed ledger technology (DLT) must address long-standing bottlenecks—particularly scalability, latency, and cross-chain interoperability. Research across Layer-1 and Layer-2 ecosystems reveals a trajectory aimed at minimizing throughput trade-offs while maintaining consensus robustness under stress scenarios, typical in post-disaster environments where network reliability is compromised.

Emerging modular frameworks—such as data availability layers decoupled from execution—are reshaping the architecture of DLTs. For example, several chains leveraging zero-knowledge validity proofs are carving a path toward compressing on-chain activity while preserving cryptographic verifiability. However, widespread adoption for disaster infrastructure will require more than technical elegance—it hinges on incorporating dynamic logic and off-chain state redundancy. Projects elevating runtime composability, like Agoric’s hardened JavaScript architecture, are already paving the way for smart contracts that can react to real-world disaster telemetry in real time. For readers interested in Agoric’s modular smart contract development, A Deepdive into Agoric offers a thorough systems-level overview.

Meanwhile, decentralized computational protocols are being reevaluated through the lens of geographic latency. Edge-native DLT nodes that can operate with intermittent internet—crucial in disaster-stricken regions—are gaining serious attention. Integration between distributed oracles, cross-region mesh networks, and local data caches are bolstering the case for hybrid consensus zones that sync intermittently but remain functional in isolation. These paradigms challenge the notion of global finality as a given in all blockchain contexts.

Interoperability is also becoming non-negotiable if these systems are to communicate across jurisdictions and operational silos. Emergent cross-chain communication standards—particularly light client integrations that bypass full trust assumptions—are critical to ensuring that emergency funds, crisis reports, and IoT telemetry can move seamlessly across chain boundaries. However, governance barriers remain, particularly around protocol upgrades in mission-critical systems. This raises systemic concerns about centralization vectors once these tools are embedded in state workflows.

Furthermore, the composability of disaster relief DAOs with broader DeFi applications is on the horizon. Merging these verticals offers the lure of preventive funding mechanisms and insurance primitives tied to real-time smart contract data feeds. Failover logic within these shared modules, however, continues to be an underexamined attack surface.

As the ecosystem continues shifting toward modular, programmable, and geo-resilient ledger infrastructures, these innovations foreshadow more fundamental tensions in how decisions will be made around protocol direction and infrastructure deployment—topics explored in depth in the upcoming section focused on decentralization and governance models.

Part 5 – Governance & Decentralization Challenges

Governance and Decentralization Challenges in Disaster-Resilient DLT Systems

Distributed Ledger Technology (DLT) holds massive potential in disaster recovery infrastructure—especially for coordination, transparency, and auditability under crisis. But the path to implementation is entangled with governance designs that can either reinforce or critically undermine the intended decentralization ethos. At the heart of these challenges are three threats: plutocratic governance, regulatory capture, and protocol-level governance attacks.

Decentralized governance models, often embodied through token-based voting, promise censorship resistance and autonomy. However, in disaster recovery use cases—where lives and critical resources are involved—governance mechanisms that favor token-rich participants may invite scenarios where majority token holders dictate emergency resource allocation. This plutocratic imbalance mirrors risks already observed in platforms like EOS, where governance power aggregated faster than decentralization narratives could account for.

The situation becomes more complex with emergency-specific DLT deployments, where multisig governance for rapid decisions might necessitate temporary centralization—opening the door to regulatory capture by governmental or supranational entities. Resilience networks that pivot toward centralized authorities during crises often fail to re-decentralize after the event. This introduces lingering governance anchoring at the state level—an anathema to trustless infrastructures.

Governance attacks also pose sizeable risks. Protocol-level exploits that compromise voting contracts can enable malicious actors to hijack emergency response functions—blocking aid or redirecting funds. Guardrails like quorum thresholds look good in theory but are notoriously brittle under low voter participation, as evidenced across many DeFi DAOs.

Comparatively, centralized governance approaches inherit efficient decision-making advantages. But they trade off system auditability and community trust. Any implementation that prioritizes administrative ease over decentralized resilience risks repeating past failures of non-transparent aid disbursement and opaque recovery procurement lifecycles.

Models like those proposed in the Nertis ecosystem attempt to avoid such extremes. Their approach blends modular governance frameworks with tiered voting permissioning, aiming to establish what their team terms “decentralized situational control.” This model attempts to blend resilience with rapid adaptability—a necessity in disaster response. For a more detailed look at their governance structure, refer to Decentralized Governance Nertis NTRS Explained.

The governance dilemma in disaster-capable DLTs isn't just about decentralization ethos—it's about adapting governance primitives that don't fold under pressure or concentrate power when transparency matters most. These concerns must be engineered concurrently with scalability strategies, which will be the focus of Part 6.

Part 6 – Scalability & Engineering Trade-Offs

Scaling Resilience: Engineering Trade-Offs in Deploying Distributed Ledger Tech for Disaster Recovery

While distributed ledger technology (DLT) offers compelling promise for decentralizing disaster response tools, implementing it at scale presents difficult trade-offs across decentralization, security, and speed. These tensions are not theoretical—they emerge starkly in protocol design, particularly when choosing consensus mechanisms and underlying architectures.

For example, Proof-of-Work (PoW) chains like Bitcoin remain unrivaled in censorship resistance, yet their low throughput and high latency are liabilities in time-sensitive disaster response scenarios. By contrast, delegating consensus via Proof-of-Stake (PoS) or Proof-of-Authority models can achieve significantly faster finality—critical for disaster data updating—but often compromise on decentralization, creating validator sets vulnerable to political coercion or regional outages.

Layer-1 architectures like Ethereum and Solana take divergent scaling paths: Ethereum leans into rollups and sharding (Layer-2 dependent); Solana favors monolithic throughput. However, high throughput platforms face higher probabilities of dropped transactions under network stress, which can be catastrophic during real-time emergency coordination.

Modularity is emerging as a middle ground. Frameworks like Cosmos and Agoric allow application-specific chains to optimize for domain needs—useful in disaster scenarios where some functions (e.g., identity verification) require immutability, while others (e.g., supply tracking) need rapid updates. Agoric’s approach, for instance, showcases composability through hardened JavaScript smart contracts on a secure runtime, tailored to economic agents and oracle integrations. For a deeper breakdown, see A Deepdive into Agoric.

Yet these modular chains introduce their own complexity: coordinating asynchronous operations across zones or parachains strains developer tooling and increases interop risks. For life-critical infrastructure, where downtime isn't tolerable, more nodes doesn't always mean more resilience. Network congestion—whether due to spam attacks or validator latency—can delay oracle feeds, compromise bridge operations, and eject unconfirmed user transactions.

Channeling disaster-relevant data through decentralized oracles also amplifies trade-offs. On-chain validation of geospatial data or relief asset inventories remains inefficient with many public chains, and optimistic rollups still rely on challenge periods that may not be acceptable in rapid-response contexts.

Selecting a L1 or L2 stack for disaster resilience involves prioritizing failure modes. Is the network acceptable to partially fail (i.e., slow down), or does it need deterministic finality under stress? A protocol that optimizes for full uptime during natural disasters may have to sacrifice self-custody or decentralization by design.

Part 7 will explore how these engineering choices intersect with regulatory friction—especially as sovereign governments demand both compliance and control from platforms designed to resist both.

Part 7 – Regulatory & Compliance Risks

Regulatory and Compliance Risks: Legal Limitations Threatening the Integration of Distributed Ledger Technology in Emergency Management Systems

The deployment of Distributed Ledger Technology (DLT) in disaster response frameworks may promise efficiency and transparency, but the regulatory terrain it faces is both fragmented and volatile. For developers and stakeholders in this space — from DAO architects to Layer-1 blockchain engineers — the regulatory burden introduces critical roadblocks that extend far beyond traditional compliance scopes.

One of the most immediate frictions is extraterritorial jurisdictional mismatches. A disaster-resilient blockchain platform built across nodes situated in the U.S., EU, and Southeast Asia, for example, could face incompatible data residency laws. The General Data Protection Regulation (GDPR) in Europe contradicts blockchain immutability, particularly concerning the "right to be forgotten." Any ledger storing sensitive responder or victim data may collide with this fundamental provision, risking massive fines or operational injunctions.

In contrast, jurisdictions like Singapore and Switzerland have carved out relatively blockchain-friendly frameworks. But even in these regions, the scope of DLT usage in public-sector infrastructure, such as emergency response coordination, remains under-regulated — leaving developers exposed to future legal reinterpretations. These discrepancies pose existential threats to cross-border deployments of DLT-based emergency systems.

Furthermore, regulators are increasingly aggressive in asserting oversight on systems that involve on-chain funding or asset disbursements — common features in disaster relief use cases. Smart contracts that program automatic distribution of emergency aid tokens could be labeled as unauthorized securities offerings or fall under money transmitter licensing requirements depending on the jurisdiction. Precedents from years of crypto litigation, including SEC-led crackdowns and the CFTC’s oversight of derivatives protocols, underscore the real-world risk of this kind of misclassification.

Government intervention remains a wildcard. In disaster scenarios, national agencies may attempt to override DLT-based decision-making in favor of centralized command, especially in times of perceived crisis. The autonomy promised by DAOs and distributed consensus mechanisms becomes politically fragile under emergency declarations — raising critical questions around operational sovereignty.

There’s also a growing interest among lawmakers to implement kill-switch requirements in critical infrastructure use cases. Such a mandate would directly oppose one of blockchain’s foundational principles: censorship resistance. Developers building permissionless DLT systems for emergency use must wrestle with compromises that may undercut long-term trust in the protocol’s integrity.

Systems like Agoric’s smart contract framework, which utilize hardened JavaScript, present innovative technical solutions but still dwell in a gray zone regarding formal compliance. Developers integrating these architectures into disaster resilience tools may find value in understanding the broader governance implications covered in Governance Unlocked: The Power of BLD in Agoric.

Part 8 will explore the financial and economic complexities of incorporating blockchain and DLT infrastructure into global disaster recovery systems — from the cost of network incentives to macroeconomic shocks caused by decentralized response funding.

Part 8 – Economic & Financial Implications

Disaster Recovery, Tokenization, and the Redistribution of Economic Power

Distributed Ledger Technology (DLT) stands to reshape not just disaster resilience systems, but the economic frameworks supporting them. As emergency response becomes programmable through smart contracts and disaster relief is tokenized, we’re witnessing the emergence of a parallel economy—one that could siphon value from traditional aid infrastructure into decentralized ecosystems. For institutional investors, this isn't just disruption; it’s an alternative asset class in incubation.

Traditional insurance markets may find themselves disintermediated by decentralized risk pools governed by DAOs. Smart contract-based parametric insurance—triggered automatically on verifiable data or oracles—threatens to bypass slow claims processes. But this efficiency introduces complex oracular dependencies. Malfunctioning or manipulated data inputs could lead to systemic capital drains rather than quick responses.

Developers and protocol architects monetizing DLT solutions in the public preparedness sector now find an incentive alignment not just in yield farming, but in impact farming. However, the capital arriving via venture funding or protocol-level incentives often brings speculative pressure—frequently at odds with the humanitarian intent of the underlying logic.

Traders, meanwhile, are already exploring niche volatility plays: speculative tokens pegged to regional disaster bonds, weather derivatives written on-chain, or even catastrophe-backed NFTs representing fractional ownership in aid infrastructure. These instruments present immense trading opportunities but introduce financialization to systems traditionally shielded from market speculative risk. This dynamic creates a new form of fragility: moral hazard in disaster anticipation.

Institutional investors, with their appetite for tokenized climate resilience assets or disaster-based ESG products, may pressure protocols into centralizing governance for predictable returns. This undermines the very decentralization these systems are built upon—a challenge also visible in governance debates around initiatives like A Deepdive into Agoric, where BLD’s role has sparked contention between decentralization purists and efficiency pragmatists.

Another overlooked consideration: state actors. As DLT-driven disaster response gains traction, governments face a difficult choice—integrate and regulate or lose fiscal sovereignty over critical infrastructure. If capital migration into disaster crypto markets becomes substantial, national funds may find themselves competing with DAOs in credibility, transparency, and even execution.

The economic terrain of disaster management is evolving into one where value capture is potentially more lucrative than value delivery. Whether this creates more resilient systems or speculative perversions remains unresolved.

Next, we’ll examine how these economic shifts trigger deeper societal and philosophical questions—redefining notions of trust, civic engagement, and moral responsibility in a post-centralized world.

Part 9 – Social & Philosophical Implications

Economic and Financial Implications of DLT in Disaster Resilience: Disruption, Opportunity, and Risk

As Distributed Ledger Technology (DLT) penetrates the emergency management sector, it’s not just reconfiguring infrastructure logic—it’s reshaping markets. The financial systems that fund disaster relief and insurance—typically reliant on intermediaries and rigid verification timelines—face fundamental disruption. DLT-based protocols can tokenize disaster risk (“cat bonds”) or enable immediate, condition-triggered relief disbursement through parametric insurance smart contracts. This disintermediates legacy reinsurers and creates new opportunities for DeFi liquidity providers willing to stake capital into high-risk, high-volatility verticals previously confined to institutional actors.

Of note is the rising interest from DeFi-native capital allocators. Traders and institutional liquidity managers are beginning to parse disaster resilience segments using the same primitives employed in yield farming and DAO governance. However, risk modeling on-chain is underdeveloped, and reliance on third-party oracle frameworks to feed real-world catastrophe data introduces vectors for manipulation or black swan failure. Projects exploring decentralized oracle models, like those featured in The Underexplored Role of Blockchain in Transforming Disaster Management, underscore this critical infrastructure gap.

Tokenization also raises economic debates around who controls crisis data and its monetization. Developers building DLT infrastructure tuned for emergency contexts may gain first-mover advantages, but they risk regulatory entanglement if disaster-proof applications conflict with privacy or sovereignty norms. Meanwhile, governance instability in high-stakes ecosystems can cause selloffs or manipulation by whales during emergencies when governance votes have real-world consequences on populations. This is especially evident in ecosystems with weak slashing mechanisms or low voter participation.

Institutional investors navigating Environmental, Social, and Governance (ESG) mandates are watching these applications closely. DLT-enabled disaster response aligns with ESG-aligned allocative logic—but only if systemic risks are transparent. Injecting capital into DAO-managed disaster insurance pools may offer returns decorrelated from macro-finance, a rare diversification vector. Yet liquidity is precarious; exit windows during large-scale disasters could vanish, leaving LPs locked in illiquid insurance derivatives or local recovery tokens.

On the upside, new investment vehicles and protocol-layer assets may be born here. Governance tokens representing disaster zones, micro-tokenized donation assets, or even reputation-based trust scoring models could create parallel economies centered on resilience capital. But this is speculative frontier territory, where social risks intertwine with financial logic—a dynamic that will be explored next, as we dissect the social and philosophical implications of DLT-enabled emergency systems.

Part 10 – Final Conclusions & Future Outlook

From Immutable Ledgers to Irreversible Change: What DLT Could Mean for Emergency Management

After examining blockchain’s underappreciated role in disaster resilience and recovery, the final synthesis is clear: distributed ledger technology (DLT) offers structural advantages that legacy systems weren’t designed to deliver. Immutable audit trails, automated fund disbursements, peer-to-peer verifiability, and decentralized identity mechanisms all have profound implications for both mitigating disaster impact and accelerating recovery efforts. And yet, the promise remains largely theoretical in practice.

This series uncovered several high-impact potential use cases—from decentralized aid distribution protocols to supply chain transparency across fragmented relief operations. However, the deepest systemic advantage may be in survivability itself: DLT networks, especially those leveraging Proof-of-Stake or scalable Layer-1 chains, can remain operational in scenarios where centralized infrastructure collapses. Here, decentralization isn’t a feature—it’s the lifeline.

The best-case scenario? Governments, NGOs, and citizen responders embrace protocol-agnostic solutions powered by cross-chain interoperability. Wallet-based identity replaces paper documentation in refugee management. Smart contracts ensure that aid flows as dynamically and accountably as conditions demand. DAOs facilitate localized governance during chaos, allowing for faster consensus and resource allocation. These systems function even when borders, bureaucracies, or telecommunications don’t.

The worst-case scenario is also within sight. Fragmentation between platforms, regulatory ambiguity, lack of disaster-specific protocol design, and insufficient user education could render solutions inaccessible or even counterproductive. If UX remains inaccessible or if integrations stay siloed in tokenization hashtags rather than tested deployments, the narrative may never shift beyond the thought leadership phase. Risk lies not in the tech, but in its deployment blindness.

Compare this to frameworks like Nertis, which already aim to apply decentralized governance to real-world contingencies. The gap between conceptual innovation and deployed utility remains massive—but not insurmountable.

Several questions remain: Who underwrites liability in autonomous relief DAOs? How are “off-chain” disasters interpreted within “on-chain” logic? Can decentralized responses operate under sovereign constraints? These are non-trivial issues, and until addressed, will likely be barriers to critical adoption.

For DLT to gain traction in critical infrastructure, incentive alignment between state institutions, enterprise software vendors, and grassroots crypto protocols must happen. Tooling must become seamless. Standards must emerge. And the pressure to be “ready before the next emergency” must outweigh the inertia of current disaster tech stacks.

The final question is a sobering one: Will DLT in disaster response be blockchain’s defining legacy—or its most compelling unrealized capability, buried beneath hype cycles and unfinished codebases?

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